Text-to-Image Generation Project

A Jupyter notebook (Texttoimage.ipynb) that demonstrates generating images from text prompts using a deep-learning text-to-image model.

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A Jupyter notebook (Text_to_image.ipynb) that demonstrates generating images from text prompts using a deep-learning text-to-image model.

Example

Open Text_to_image.ipynb in Jupyter and run the setup cells to load the model.
Locate the cell that defines the text prompt and set it to a description such as "a sunset over the ocean".
Run the generation cell — the model processes the prompt and produces an image.
The generated image is displayed inline in the notebook output below the cell.
Change the prompt to a different description and re-run the cell to generate a new image.

Open the notebook in Jupyter:

jupyter notebook Text_to_image.ipynb

Install the deep-learning dependencies referenced inside the notebook (e.g. diffusers, torch, transformers).

Deep-learning libraries such as diffusers, torch, and transformers (see the notebook cells).